LoRa + transmission network equipment fault diagnosis method and device

Abstract

The invention relates to the technical field of network fault analysis, in particular to a fault diagnosis method and device for LoRa + transmission network equipment. The method comprises the following steps: acquiring diagnosis parameters in a data acquisition server and an A2 database; and when the instrument state is offline, analyzing the diagnosis parameters according to a preset fault diagnosis rule, and outputting an equipment fault diagnosis result. Based on the 15 types of diagnosis parameters and the preset fault diagnosis rule, the specific equipment fault content is quickly and accurately diagnosed, efficient monitoring of the oil field LoRa + transmission network equipment is achieved, the fault analysis process is simplified, corresponding processing suggestions can be searched according to the output equipment fault diagnosis result, and the fault diagnosis efficiency is improved. Maintenance personnel can process faults accurately and efficiently according to processing suggestions, fault processing time is shortened, and the online rate of the instrument is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of network fault analysis, in particular to a method and a device for diagnosing faults of LoRa+ transmission network equipment. Background Art

[0002] The existing LoRa+ wireless network, including hardware and software, comes from the company "Eisen Intelligence". The LoRa+ network monitoring platform has two parts: one is SenzFlow, which provides three status parameters of the instrument: signal strength, signal-to-noise ratio, and whether it is online; the other is loraFlow.io, which provides data at the bottom layer and is relatively complicated. It requires a deep understanding of the operating mechanism of the LoRa+ network to extract effective frequency points, spreading factors, signal strength, signal-to-noise ratio, and four status parameters from the complicated data. The steps for handling instrument failures usually include 1. Check whether the device is online; 2. Reset the device if it is offline; 3. Replace the device if the reset has not yet recovered; if it is a gateway failure or network coverage problem, even replacing the device cannot eliminate the fault.

[0003] The existing LoRa+ transmission network monitoring platform has scattered device status data, and the management tools it provides have single functions. Some of the data obtained are relatively professional and do not support centralized display. Fault analysis requires multiple use of tools to obtain relevant data, which places high technical requirements on maintenance personnel. At the same time, the LoRa+ monitoring platform provides fewer device status parameters and cannot meet the needs of fault judgment. That is, when a device fails, you can only see that the device status is offline, and you cannot know the specific reason for the device being offline. If you don’t know the reason for the offline, you can’t quickly handle the fault. You can only use common fault handling methods in sequence based on experience, which greatly prolongs the fault handling time and sometimes makes the fault unhandled. Summary of the invention

[0004] The present invention provides a LoRa+ transmission network equipment fault diagnosis method and device, which overcomes the shortcomings of the above-mentioned prior art and can effectively solve the problem that the existing LoRa+ transmission network equipment fault diagnosis method can only determine whether the device is offline due to the small number of parameters used for diagnosis, but cannot accurately diagnose the specific fault content.

[0005] One of the technical solutions of the present invention is achieved by the following measures: a LoRa+ transmission network equipment fault diagnosis method, comprising: Collect diagnostic parameters in the data acquisition server and A2 database, including the best gateway, number of retransmissions, number of resets, whether a single well has a gateway, single well gateway status, production status, single well strongest signal, online rate, number of disconnections, frequency, spreading factor, signal strength, signal-to-noise ratio, gateway status, and instrument status; When the instrument is in offline state, the diagnostic parameters are analyzed according to the preset fault diagnosis rules and the equipment fault diagnosis results are output.

[0006] The following are further optimizations and / or improvements to the above technical solutions: The above fault diagnosis rules include: If the instrument is offline and a single well has a gateway and the single well gateway is offline, it means that a single well gateway failure has occurred; If the instrument is offline and the strongest signal of a single well is <-120dB and there is no gateway in the single well, it means that there is a network coverage problem; If the instrument is offline and the strongest signal in a single well is > -110dB, it means that the equipment antenna or battery is faulty; If the instrument offline and online rate is >95%, it means that an occasional failure has occurred; If the instrument is offline and the production status is shut-in, it means that offline has occurred but no processing is required; If the meter is offline and the single well has a gateway and the single well gateway is online, it means that there is no connection to the best gateway; If the instrument is offline and the online rate is <50% and the number of offline times is >10, it means that frequent offline occurs.

[0007] The above also includes searching for corresponding processing suggestions according to the output device fault diagnosis results. If the corresponding processing suggestions fail to be found, the staff will handle it independently and then manually enter the corresponding processing suggestions.

[0008] The above also includes diversified data display, where diversified data display includes dynamic display of collected diagnostic parameters, viewing fault diagnosis results and corresponding processing suggestions.

[0009] The diagnostic parameters collected in the data acquisition server and A2 database include: Collect real-time data in the data acquisition server; Get log notes in A2 database; Directly capture the frequency point, spreading factor, signal strength, signal-to-noise ratio, gateway status, and instrument status in real-time data and log notes; use analytical calculations to indirectly capture the best gateway, number of retransmissions, number of resets, whether a single well has a gateway, single well gateway status, production status, single well strongest signal, online rate, and number of disconnections in real-time data and log notes.

[0010] The second technical solution of the present invention is achieved by the following measures: a LoRa+ transmission network equipment fault diagnosis device, comprising: The parameter collection unit collects diagnostic parameters in the data collection server and A2 database, including the best gateway, number of retransmissions, number of resets, whether a single well has a gateway, the status of a single well gateway, production status, the strongest signal of a single well, online rate, number of disconnections, frequency, spreading factor, signal strength, signal-to-noise ratio, gateway status, and instrument status; The fault analysis unit analyzes the diagnostic parameters according to the preset fault diagnosis rules when the instrument is offline, and outputs the equipment fault diagnosis results; The fault handling knowledge base stores fault diagnosis rules, equipment fault diagnosis results, and collected diagnostic parameters.

[0011] The following are further optimizations and / or improvements to the above technical solutions: The above-mentioned fault analysis unit comprises: The fault diagnosis module analyzes the diagnostic parameters according to the preset fault diagnosis rules when the instrument is offline, and outputs the equipment fault diagnosis results; The processing suggestion matching module searches for the corresponding processing suggestion based on the output device fault diagnosis result. If the search for the corresponding processing suggestion fails, the staff will handle it independently and then manually enter the corresponding processing suggestion.

[0012] The above also includes a human-computer interaction unit for diversified data display and manual data entry by staff, where the diversified data display includes dynamic display of collected diagnostic parameters, viewing of fault diagnosis results and corresponding processing suggestions.

[0013] In the present invention, diagnostic parameters are collected in the data acquisition server and the A2 database. On the basis of the original frequency point, spread spectrum factor, signal strength, signal-to-noise ratio, gateway status, and instrument status, 9 more diagnostic parameters are added, namely, the best gateway, number of retransmissions, number of resets, whether a single well has a gateway, the status of a single well gateway, production status, the strongest signal of a single well, online rate, and number of disconnections. Based on 15 types of diagnostic parameters and pre-set fault diagnosis rules, the specific equipment fault content is quickly and accurately diagnosed, and efficient monitoring of the oil field LoRa+ transmission network equipment is achieved, the fault analysis process is simplified, and the existing method for LoRa+ transmission network equipment fault diagnosis that relies only on 6 types of diagnostic parameters is solved. Due to the small number of parameters used for diagnosis, it can only determine whether the equipment status is offline, and cannot accurately diagnose the specific fault content. Further, the present invention can also find the corresponding processing suggestions according to the output device fault diagnosis results, and the maintenance personnel can accurately and efficiently handle the fault according to the processing suggestions, shorten the fault handling time, and improve the instrument online rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Attached Figure 1The figure is a flow chart of a diagnostic method of the present invention.

[0015] Attached Figure 2 The figure is a flow chart of another diagnostic method of the present invention.

[0016] Attached Figure 3 It is a schematic diagram of the structure of a diagnostic device of the present invention.

[0017] Attached Figure 4 This is a schematic diagram of the structure of another diagnostic device of the present invention. DETAILED DESCRIPTION

[0018] The present invention is not limited by the following embodiments, and specific implementation methods can be determined based on the technical solution of the present invention and actual conditions.

[0019] The present invention will be further described below in conjunction with embodiments and drawings: Embodiment 1: As attached Figure 1 As shown, an embodiment of the present invention discloses a LoRa+ transmission network device fault diagnosis method, comprising: Step S110, collecting diagnostic parameters in the data acquisition server and A2 database, wherein the diagnostic parameters include the best gateway, number of retransmissions, number of resets, whether a single well has a gateway, single well gateway status, production status, single well strongest signal, online rate, number of disconnections, frequency, spreading factor, signal strength, signal-to-noise ratio, gateway status, and instrument status; Step S120, when the instrument is in an offline state, the diagnostic parameters are analyzed according to preset fault diagnosis rules, and the equipment fault diagnosis result is output.

[0020] In the present invention, diagnostic parameters are collected in a data acquisition server and an A2 database. On the basis of the original six types of diagnostic parameters, namely, frequency, spread spectrum factor, signal strength, signal-to-noise ratio, gateway status, and instrument status, nine more types of diagnostic parameters are added, namely, the best gateway, number of retransmissions, number of resets, whether a single well has a gateway, single well gateway status, production status, single well strongest signal, online rate, and number of offline times. Based on 15 types of diagnostic parameters and pre-set fault diagnosis rules, specific equipment fault contents are diagnosed quickly and accurately, and efficient monitoring of oilfield LoRa+ transmission network equipment is achieved, the fault analysis process is simplified, the fault handling time is shortened, and the instrument online rate is improved. The problem that the existing method for diagnosing LoRa+ transmission network equipment faults that relies on only six types of diagnostic parameters can only determine whether the equipment status is offline, but cannot accurately diagnose the specific fault contents due to the small number of parameters used for diagnosis.

[0021] Embodiment 2: The embodiment of the present invention discloses a LoRa+ transmission network equipment fault diagnosis method, comprising: Step S210, collecting diagnostic parameters in the data acquisition server and the A2 database, wherein the diagnostic parameters include the best gateway, number of retransmissions, number of resets, whether a single well has a gateway, the state of a single well gateway, production status, the strongest signal of a single well, online rate, number of disconnections, frequency, spreading factor, signal strength, signal-to-noise ratio, gateway state, and instrument state; The diagnostic parameters collected in the data acquisition server and A2 database include: (1) Collect real-time data in the data acquisition server; (2) Obtain log notes in the A2 database; (3) Directly capture the frequency point, spreading factor, signal strength, signal-to-noise ratio, gateway status, and instrument status in real-time data and log notes; use analytical calculations to indirectly capture the best gateway, number of retransmissions, number of resets, whether a single well has a gateway, single well gateway status, production status, single well strongest signal, online rate, and number of disconnections in real-time data and log notes.

[0022] Step S220, when the instrument is in an offline state, the diagnostic parameters are analyzed according to preset fault diagnosis rules, and the equipment fault diagnosis result is output.

[0023] In the above steps, the fault diagnosis rules include: If the instrument is offline and a single well has a gateway and the single well gateway is offline, it means that a single well gateway failure has occurred; If the instrument is offline and (the strongest signal in a single well is <-120dB) and there is no gateway in a single well, it means that there is a network coverage problem; If the instrument is offline and (the strongest signal in a single well is > -110dB), it means that the equipment antenna or battery is faulty; If the instrument is offline and (online rate > 95%), it means that an occasional failure has occurred; If the instrument is offline and the production status is shut-in, it means that offline has occurred but no processing is required; If the meter is offline and the single well has a gateway and the single well gateway is online, it means that there is no connection to the best gateway; If the instrument is offline and (online rate <50%) and (offline times >10), it means frequent offline.

[0024] The content of the fault diagnosis rules here can also be adjusted according to actual conditions.

[0025] Embodiment 3: As attached Figure 2 As shown, an embodiment of the present invention discloses a LoRa+ transmission network device fault diagnosis method, comprising: Step S310, collecting diagnostic parameters in the data acquisition server and A2 database, wherein the diagnostic parameters include the best gateway, number of retransmissions, number of resets, whether a single well has a gateway, single well gateway status, production status, single well strongest signal, online rate, number of disconnections, frequency, spreading factor, signal strength, signal-to-noise ratio, gateway status, and instrument status; Step S320, when the instrument is in an offline state, the diagnostic parameters are analyzed according to the preset fault diagnosis rules, and the equipment fault diagnosis results are output; Step S330, after the device fault diagnosis result is output, a corresponding processing suggestion is searched according to the device fault diagnosis result. If the search for the corresponding processing suggestion fails, the staff member manually enters the corresponding processing suggestion after autonomous processing; Step S340, performing diversified data display, wherein the diversified data display includes dynamically displaying the collected diagnostic parameters, viewing the fault diagnosis results and corresponding processing suggestions.

[0026] In the above steps, the corresponding processing suggestions are found according to the output device fault diagnosis results. Here, processing suggestions for various types of equipment failures are manually entered and stored in advance (processing suggestions can be given by experts or summarized by staff). They can be identified one by one using identification codes, or equipment failures and processing suggestions can be tabulated to facilitate subsequent automatic and rapid matching of corresponding processing suggestions according to equipment failures. Maintenance personnel can accurately and efficiently handle faults according to the processing suggestions, shorten fault handling time, and improve instrument online rate.

[0027] Embodiment 4: As attached Figure 3 As shown, an embodiment of the present invention discloses a LoRa+ transmission network equipment fault diagnosis device, comprising: The parameter collection unit collects diagnostic parameters in the data collection server and A2 database, including the best gateway, number of retransmissions, number of resets, whether a single well has a gateway, the status of a single well gateway, production status, the strongest signal of a single well, online rate, number of disconnections, frequency, spreading factor, signal strength, signal-to-noise ratio, gateway status, and instrument status; The fault analysis unit analyzes the diagnostic parameters according to the preset fault diagnosis rules when the instrument is offline, and outputs the equipment fault diagnosis results; The fault analysis unit includes: The fault diagnosis module analyzes the diagnostic parameters according to the preset fault diagnosis rules when the instrument is offline, and outputs the equipment fault diagnosis results; The processing suggestion matching module searches for the corresponding processing suggestion according to the output device fault diagnosis result. If the search for the corresponding processing suggestion fails, the staff will handle it independently and then manually enter the corresponding processing suggestion. The fault handling knowledge base stores fault diagnosis rules, equipment fault diagnosis results, and collected diagnostic parameters.

[0028] Embodiment 5: As attached Figure 4 As shown, an embodiment of the present invention discloses a LoRa+ transmission network equipment fault diagnosis device, comprising: The parameter collection unit collects diagnostic parameters in the data collection server and A2 database, including the best gateway, number of retransmissions, number of resets, whether a single well has a gateway, the status of a single well gateway, production status, the strongest signal of a single well, online rate, number of disconnections, frequency, spreading factor, signal strength, signal-to-noise ratio, gateway status, and instrument status; The fault analysis unit analyzes the diagnostic parameters according to the preset fault diagnosis rules when the instrument is offline, and outputs the equipment fault diagnosis results; Fault handling knowledge base, which stores fault diagnosis rules, equipment fault diagnosis results, and collected diagnostic parameters; The human-computer interaction unit performs diversified data display and manual data entry by staff. The diversified data display includes dynamic display of collected diagnostic parameters, viewing of fault diagnosis results and corresponding processing suggestions.

[0029] The above-mentioned human-computer interaction unit may be a monitoring board.

[0030] The above technical features constitute the best embodiment of the present invention, which has strong adaptability and best implementation effect. Non-essential technical features can be added or reduced according to actual needs to meet the requirements of different situations.

Claims

1. A LoRa+ transmission network equipment fault diagnosis method, characterized in that: include: Collect diagnostic parameters in the data acquisition server and A2 database, including the best gateway, number of retransmissions, number of resets, whether a single well has a gateway, single well gateway status, production status, single well strongest signal, online rate, number of disconnections, frequency, spreading factor, signal strength, signal-to-noise ratio, gateway status, and instrument status; When the instrument is in offline state, the diagnostic parameters are analyzed according to the preset fault diagnosis rules and the equipment fault diagnosis results are output.

2. The LoRa+ transmission network equipment fault diagnosis method according to claim 1, characterized in that, The fault diagnosis rules include: If the instrument is offline and a single well has a gateway and the single well gateway is offline, it means that a single well gateway failure has occurred; If the instrument is offline and the strongest signal of a single well is <-120dB and there is no gateway in the single well, it means that there is a network coverage problem; If the instrument is offline and the strongest signal in a single well is > -110dB, it means that the equipment antenna or battery is faulty; If the instrument offline and online rate is >95%, it means that an occasional failure has occurred; If the instrument is offline and the production status is shut-in, it means that offline has occurred but no processing is required; If the instrument is offline and the single well has a gateway and the single well gateway is online, it means that there is no connection to the best gateway; If the instrument is offline and the online rate is <50% and the number of offline times is >10, it means that frequent offline occurs.

3. The LoRa+ transmission network equipment fault diagnosis method according to claim 1 or 2, characterized in that, It also includes searching for corresponding processing suggestions based on the output device fault diagnosis results. If the corresponding processing suggestions fail to be found, the staff will handle it independently and then manually enter the corresponding processing suggestions.

4. The LoRa+ transmission network equipment fault diagnosis method according to claim 1 or 2, characterized in that, It also includes diversified data display, including dynamic display of collected diagnostic parameters, viewing fault diagnosis results and corresponding processing suggestions.

5. The LoRa+ transmission network equipment fault diagnosis method according to claim 3, characterized in that: It also includes diversified data display, including dynamic display of collected diagnostic parameters, viewing fault diagnosis results and corresponding processing suggestions.

6. The LoRa+ transmission network equipment fault diagnosis method according to any one of claims 1 to 5, characterized in that: The collecting of diagnostic parameters in the data acquisition server and the A2 database includes: Collect real-time data in the data acquisition server; Get log notes in A2 database; Directly capture the frequency point, spreading factor, signal strength, signal-to-noise ratio, gateway status, and instrument status in real-time data and log notes; use analytical calculations to indirectly capture the best gateway, number of retransmissions, number of resets, whether a single well has a gateway, single well gateway status, production status, single well strongest signal, online rate, and number of disconnections in real-time data and log notes.

7. A LoRa+ transmission network equipment fault diagnosis device using the method according to any one of claims 1 to 6, characterized in that: include: The parameter collection unit collects diagnostic parameters in the data collection server and A2 database, including the best gateway, number of retransmissions, number of resets, whether a single well has a gateway, the status of a single well gateway, production status, the strongest signal of a single well, online rate, number of disconnections, frequency, spreading factor, signal strength, signal-to-noise ratio, gateway status, and instrument status; The fault analysis unit analyzes the diagnostic parameters according to the preset fault diagnosis rules when the instrument is offline, and outputs the equipment fault diagnosis results; The fault handling knowledge base stores fault diagnosis rules, equipment fault diagnosis results, and collected diagnostic parameters.

8. The LoRa+ transmission network equipment fault diagnosis device according to claim 7, characterized in that: The fault analysis unit comprises: The fault diagnosis module analyzes the diagnostic parameters according to the preset fault diagnosis rules when the instrument is offline, and outputs the equipment fault diagnosis results; The processing suggestion matching module searches for the corresponding processing suggestion based on the output device fault diagnosis result. If the search for the corresponding processing suggestion fails, the staff will handle it independently and then manually enter the corresponding processing suggestion.

9. The LoRa+ transmission network equipment fault diagnosis device according to claim 7 or 8, characterized in that: It also includes a human-computer interaction unit for diversified data display and manual data entry by staff. The diversified data display includes dynamic display of collected diagnostic parameters, viewing of fault diagnosis results and corresponding processing suggestions.

Images